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White oak mortality is a significant concern in forest ecosystems due to its impact on biodiversity and ecosystem functions. Understanding the factors influencing white oak mortality is crucial for effective forest management and conservation efforts. In this study, we aimed to investigate the spatial pattern of WOM rates across the eastern US and explore the underlying processes behind the observed spatial patterns. Multicycle forest inventory and analysis data were compiled to capture all white oak plots. WOM data were selected across plot systems that utilized declining basal areas between two periods. Ripley's K function was used to study the spatial pattern of WOM rates. Results showed clustered patterns of WOM rates at local and broad scales that may indicate stand-level competition and regional variables affecting white oaks' dynamics across southern and northern regions. Results also indicated random patterns at broad scales, suggesting variations in topographic and hydrological conditions across the south and northern regions. However, the central region indicated both clustered and random patterns at the local scale that might be associated with inter-species competition and the possibility of environmental heterogeneity, respectively. Furthermore, uniform patterns of WOM rate at a broad scale across all regions might suggest regions with spatially homogeneous environmental factors acting on the dynamics of white oaks. This research might be helpful in identifying impacted areas of white oaks at varying scales. Future research is needed to comprehensively assess biotic and abiotic factors at various spatial scales aimed at mitigating WOM. [ABSTRACT FROM AUTHOR]

Abstract This article investigates the role of the spatial dimension in the formulation of pandemic rules in Italy, with a specific focus on the municipal ordinances enacted in Milan. The study conducts a critical review of multidisciplinary literature, which often marginalises the significance of spatial dynamics in the development of (pandemic) regulatory frameworks, relegating “space” to a peripheral rather than central concern. This research proposes an analytical framework to evaluate spatial rules based on key thematic categories, with reference to the application and structural attributes of pandemic regulations. The article also discusses the practical integration of spatial dimensions into regulatory design, emphasising the imperative of acknowledging and engaging with unique spatial characteristics in order to enhance the efficacy of legal and policy interventions.

This article investigates the role of the spatial dimension in the formulation of pandemic rules in Italy, with a specific focus on the municipal ordinances enacted in Milan. The study conducts a critical review of multidisciplinary literature, which often marginalises the significance of spatial dynamics in the development of (pandemic) regulatory frameworks, relegating "space" to a peripheral rather than central concern. This research proposes an analytical framework to evaluate spatial rules based on key thematic categories, with reference to the application and structural attributes of pandemic regulations. The article also discusses the practical integration of spatial dimensions into regulatory design, emphasising the imperative of acknowledging and engaging with unique spatial characteristics in order to enhance the efficacy of legal and policy interventions. [ABSTRACT FROM AUTHOR]

There are various types of land use in the agricultural and pastoral areas of northern China, including natural grassland and artificial grassland, scrub land, forest land and farmland, may change the soil microbial community However, the soil microbial communities in these different land use types remain poorly understood. In this study, we compared soil microbial communities in these five land use types within the agro-pastoral ecotone of northern China. Our results showed that land use has had a considerable impact on soil bacterial and fungal community structures. Bacterial diversity was highest in shrubland and lowest in natural grassland; fungal diversity was highest in woodland. Microbial network structural complexity also differed significantly among land use types. The lower complexity of artificial grassland and farmland may be a result of the high intensity of anthropogenic activities in these two land-use types, while the higher structural complexity of the shrubland and woodland networks characterised by low-intensity management may be a result of low anthropogenic disturbance. Correlation analysis of soil properties (e.g., soil physicochemical properties, soil nutrients, and microbiomass carbon and nitrogen levels) and soil microbial communities demonstrated that although microbial taxa were correlated to some extent with soil environmental factors, these factors did not sufficiently explain the microbial community differences among land use types. Understanding variability among soil microbial communities within agropastoral areas of northern China is critical for determining the most effective land management strategies and conserving microbial diversity at the regional level. [ABSTRACT FROM AUTHOR]

The frequent outbreaks of European spruce bark beetle Ips typographus (L.) have destroyed huge amounts of Norway spruce Picea abies (L.) forests in central and Northern Europe. Identifying the risk factors and estimating the damage level is important for strategic damage control. The risk factors of forest damage by spruce bark beetles have mostly been analyzed on the landscape scale, while the in-stand risk factors have been less investigated. This study aims at exploring the local-scale risk factors in a flat area with spruce-dominated forest in southern Sweden. The investigated factors include four abiotic factors, i.e., soil wetness, solar radiation, slope gradient, and aspect, and three biotic factors, i.e., the number of deciduous trees and trees that died from attacks in previous years that remained (TreesLeft) and removed (TreesRemoved) from the forest stand. We put up 24 pheromone bags in six stands attacked by bark beetle in the previous years, resulting in different numbers of infested trees in each plot. We explored in which microenvironment a pheromone bag resulted in more colonization, the impact radius of each factor, and the necessary factors for a risk model. The environmental factors were obtained from remote sensing-based products and images. A generalized linear model (GLM) was used with the environmental factors as the explanatory variables and the damage levels as the response variables, i.e., the number of attacked trees for the plot scale, and healthy/infested for the single-tree scale. Using 50 m and 15 m radius of the environmental factors resulted in the best fit for the model at plot and individual tree scales, respectively. At those radii, the damage risk increased both at plot and individual tree level when spruce were surrounded by more deciduous trees, surrounded by dead trees that had been removed from the forest, and spruces located at the north and east slopes (315°–135° of aspect, > 2° slope). Soil wetness, solar radiation, and remaining standing dead trees in the surrounding did not significantly impact the damage level in the microenvironment of the study area. The GLM risk model yielded an overall accuracy of 0.69 in predicting individual trees being infested or healthy. Our efforts to investigate the risk factors provide a context for wall-to-wall mapping in-stand infestation risks, using remote sensing-based data. [ABSTRACT FROM AUTHOR]

Wetland reclamation was an intrinsic part of nineteenth-century global agricultural transformations. In Swedish research, reclamation has mainly been situated in larger general processes of population rise, commercialization and societal/technological development. The intersection of reclamation, physical environments and local economies has seldom been studied in detail. This paper conducts a local analysis of nineteenth-century wetland reclamation in two parishes in Sweden, Knätte and Mörlunda, through combining a study of specific reclamation processes with an analysis of local agrarian-economic development. The results show that these processes varied depending on specific historical-geographical circumstances. In Knätte, reclamation was not primarily related to population rise, but to increasing commercialization during the period. The case in Mörlunda instead shows how reclamation was first a response to increasing population but later developed into a project of agricultural market adaptation. In both cases, the physical environment led to varying degrees of geographic constraint in the process. In combination, these results point to the importance of detailed case studies in nuancing our understanding of nineteenth-century wetland reclamation both in Sweden and internationally. • Local factors are important for nuancing general trends in wetland reclamation. • In Sweden, population rise and commercialization are considered primary drivers. • The active drivers vary between the compared cases, depending on context. • Reclamation was primarily a part of local agrarian developments. • Wider relations of the local economy, for example through trade, also impacted. [ABSTRACT FROM AUTHOR]

Abstract Background Infectious diseases are emerging across temperate regions of the world, and, for some, links have been made between landscapes and emergence dynamics. For tick-borne diseases, public parks may be important exposure sites for people living in urbanized areas of North America and Europe. In most cases, we know more about the ecological processes that determine the hazard posed by ticks as disease vectors than we do about how human population exposure varies in urban natural parks. Methods In this study, infrared counters were used to monitor visitor use of a public natural park in southern Quebec, Canada. A risk index representing the probability of encounters between humans and infected vectors was constructed. This was done by combining the intensity of visitor trail use and the density of infected nymphs obtained from field surveillance. Patterns of risk were examined using spatial cluster analysis. Digital forest data and park infrastructure data were then integrated using spatially explicit models to test whether encounter risk levels and its components vary with forest fragmentation indicators and proximity to park infrastructure. Results Results suggest that, even at a very fine scales, certain landscape features and infrastructure can be predictors of risk levels. Both visitors and Borrelia burgdorferi-infected ticks concentrated in areas where forest cover was dominant, so there was a positive association between forest cover and the risk index. However, there were no associations between indicators of forest fragmentation and risk levels. Some high-risk clusters contributed disproportionately to the risk distribution in the park relative to their size. There were also two high-risk periods, one in early summer coinciding with peak nymphal activity, and one in early fall when park visitation was highest. Conclusions Here, we demonstrate the importance of integrating indicators of human behaviour visitation with tick distribution data to characterize risk patterns for tick-borne diseases in public natural areas. Indeed, understanding the environmental determinants of human-tick interactions will allow organisations to deploy more effective risk reduction interventions targeted at key locations and times, and improve the management of public health risks associated with tick-borne diseases in public spaces.

Background: Infectious diseases are emerging across temperate regions of the world, and, for some, links have been made between landscapes and emergence dynamics. For tick-borne diseases, public parks may be important exposure sites for people living in urbanized areas of North America and Europe. In most cases, we know more about the ecological processes that determine the hazard posed by ticks as disease vectors than we do about how human population exposure varies in urban natural parks. Methods: In this study, infrared counters were used to monitor visitor use of a public natural park in southern Quebec, Canada. A risk index representing the probability of encounters between humans and infected vectors was constructed. This was done by combining the intensity of visitor trail use and the density of infected nymphs obtained from field surveillance. Patterns of risk were examined using spatial cluster analysis. Digital forest data and park infrastructure data were then integrated using spatially explicit models to test whether encounter risk levels and its components vary with forest fragmentation indicators and proximity to park infrastructure. Results: Results suggest that, even at a very fine scales, certain landscape features and infrastructure can be predictors of risk levels. Both visitors and Borrelia burgdorferi-infected ticks concentrated in areas where forest cover was dominant, so there was a positive association between forest cover and the risk index. However, there were no associations between indicators of forest fragmentation and risk levels. Some high-risk clusters contributed disproportionately to the risk distribution in the park relative to their size. There were also two high-risk periods, one in early summer coinciding with peak nymphal activity, and one in early fall when park visitation was highest. Conclusions: Here, we demonstrate the importance of integrating indicators of human behaviour visitation with tick distribution data to characterize risk patterns for tick-borne diseases in public natural areas. Indeed, understanding the environmental determinants of human-tick interactions will allow organisations to deploy more effective risk reduction interventions targeted at key locations and times, and improve the management of public health risks associated with tick-borne diseases in public spaces. [ABSTRACT FROM AUTHOR]

Local biodiversity monitoring is important to assess the effects of global change, but also to evaluate the performance of landscape and wildlife protection, since large-scale assessments may buffer local fluctuations, rare species tend to be underrepresented, and management actions are usually implemented on local scales. We estimated population trends of 58 bird species using open-population N-mixture models based on count data in two localities in southeastern Spain, which have been collected according to a citizen science monitoring program (SACRE, Monitoring Common Breeding Birds in Spain) over 21 and 15 years, respectively. We performed different abundance models for each species and study area, accounting for imperfect detection of individuals in replicated counts. After selecting the best models for each species and study area, empirical Bayes methods were used for estimating abundances, which allowed us to calculate population growth rates (λ) and finally population trends. We also compared the two local population trends and related them with national and European trends, and species functional traits (phenological status, dietary, and habitat specialization characteristics). Our results showed increasing trends for most species, but a weak correlation between populations of the same species from both study areas. In general, local population trends were consistent with the trends observed at national and continental scales, although contrasting patterns exist for several species, mainly with increasing local trends and decreasing Spanish and European trends. Moreover, we found no evidence of a relationship between population trends and species traits. We conclude that using open-population N-mixture models is an appropriate method to estimate population trends, and that citizen science-based monitoring schemes can be a source of data for such analyses. This modeling approach can help managers to assess the effectiveness of their actions at the local level in the context of global change. [ABSTRACT FROM AUTHOR]

Purpose: The local dimension of toxicity effect on humans and ecosystem from chemical emissions into rural environments is currently not considered in impact characterization models underlying the Life Cycle Assessment (LCA) methodology. The aim of the present study was to understand the relevance of considering a local exposure environment for the magnitude of damage related to human toxicity and ecotoxicity impacts associated with chemical emissions into a local environment. Method: Unit and realistic European emission scenarios were considered in a proposed multimedia nested box model, based on an existing framework modified with the inclusion of a local scale, and tested for ten chemicals in an illustrative case study. Results: A substantial damage increase in terms of characterization factors in the proposed model was found for human health, mainly for local freshwater emissions (up to three orders of magnitude compared to emissions into continental freshwater for naphthalene) and soil emissions (up to two orders of magnitude, in particular for emissions into natural soil for 1,2-dichloroethane). Conclusions: Based on our results, we suggest to use the proposed framework in LCA applications, when more specific information about the local emission environment is known. With respect to considering the local-scale, however, spatialized models might be preferable over nested box models to properly capture local phenomena in rather highly densely populated areas. [ABSTRACT FROM AUTHOR]

Recent seismic events and the damages related to them have highlighted the crucial role of urban planning in coping with the fragility and intrinsic vulnerability of cities. The paper presents a methodology for assessing seismic risk at an urban scale, expanding from a single-building investigation to an urban-scale analysis by adopting an empirical method for assessing the vulnerability of the urban fabric. Data collection and analysis have been conducted through the Geographic Information System (GIS). The methodology has been applied to the Italian city of Castelfranco Emilia, in the Emilia-Romagna region, where the current regional urban planning law is guiding municipalities towards the development of strategies mostly oriented toward the retrofit of the existing building stock and the overall regeneration of the urbanized territory, in accordance with the target of no net land take by 2050. The novelty of the method stands in the transposition of approaches born in the civil engineering and protection domains to the urban planning sphere, stressing the importance of developing urban planning instruments which are well-integrated with vulnerability assessments and, therefore, able to successfully incorporate risk considerations in the decision making. [ABSTRACT FROM AUTHOR]

Recently, security protection is import in many scenarios. Occluded person re-identification (Re-ID) involves identifying obscured pedestrians from images captured by multiple cameras, even when the images are partially or fully occluded. Many state-of-the-art models for occluded Re-ID utilize auxiliary modules such as pose estimation, feature pyramid, and graph matching to address occlusion challenges. However, this approach results in complex models that struggle to generalize to diverse occlusions and may not effectively handle non-occluded pedestrians. Furthermore, real-world Re-ID applications frequently involve both occluded and non-occluded pedestrians, making it difficult to develop versatile models. To tackle these issues, we introduce a novel Re-ID model that learns discriminative features on both local and global scales for occluded pedestrian identification. Our proposed model, the Local-aware Transformer (LAT) for occluded person Re-ID, comprises three modules: a Discriminative Feature Extraction Module (DFEM), a Local Feature Extraction Module (LFEM), and a Global Feature Extraction Module (GFEM). Our experimental results on three occluded and two general Re-ID benchmarks demonstrate that our model surpasses existing state-of-the-art methods and achieves exceptional performance in both occluded and non-occluded Re-ID tasks.

The assessment of vulnerability to the danger of flooding, with a focus on the need for rescue and assistance from the population, is still in an exploratory scientific phase. The main objective of this research is to propose a methodology based on the issues of rescue and assistance in the face of the risk of floods and to provide a tool for its management. A series of maps is presented, indicating those territorial elements that require rescue and surveillance in a prioritized manner in a visual and accessible way for public administration. Four methodological cartographic proposals have been designed as follows: (1) a map of territory sectors with special rescue needs (dependent population and/or buildings without shelter); a map of the impact on transportation infrastructure and vulnerable areas of buildings (2); a map of vulnerability to possible disorder and looting caused by flooding events (3); and a map of the increase in the cost of deployment for rescue and assistance systems (4). As an experimental zone to test the effectiveness of these proposals, a peri-urban area of the municipality of Málaga (Spain) is chosen, which has an extensive history of severe floods. The results confirm the applied and preventive nature of the tool, which can be incorporated into flood risk management plans and local flood risk action plans developed by public administrations. The main finding of the research is the technical advancement that comes with a precise understanding of vulnerability and its resulting issues for better flood risk management. [ABSTRACT FROM AUTHOR]

Recently, security protection is import in many scenarios. Occluded person re-identification (Re-ID) involves identifying obscured pedestrians from images captured by multiple cameras, even when the images are partially or fully occluded. Many state-of-the-art models for occluded Re-ID utilize auxiliary modules such as pose estimation, feature pyramid, and graph matching to address occlusion challenges. However, this approach results in complex models that struggle to generalize to diverse occlusions and may not effectively handle non-occluded pedestrians. Furthermore, real-world Re-ID applications frequently involve both occluded and non-occluded pedestrians, making it difficult to develop versatile models. To tackle these issues, we introduce a novel Re-ID model that learns discriminative features on both local and global scales for occluded pedestrian identification. Our proposed model, the Local-aware Transformer (LAT) for occluded person Re-ID, comprises three modules: a Discriminative Feature Extraction Module (DFEM), a Local Feature Extraction Module (LFEM), and a Global Feature Extraction Module (GFEM). Our experimental results on three occluded and two general Re-ID benchmarks demonstrate that our model surpasses existing state-of-the-art methods and achieves exceptional performance in both occluded and non-occluded Re-ID tasks. [ABSTRACT FROM AUTHOR]

Local-scale analysis and understanding of long-term spatio-temporal climatic patterns are crucial for designing site-specific climate change adaptation strategies in the Ethiopian Arabica coffee context. We conducted a comprehensive examination of long-term spatio-temporal trends and variability of rainfall and temperature during different phenological stages of Arabica coffee growth across elevation zones in five major coffee-growing districts of southwestern Ethiopia. Employing Mann–Kendall tests, Sen's slopes, coefficients of variation, and anomalies, we identified a significant increasing trend (P ≤ 0.05) in mean annual and seasonal rainfall at a rate of 5.09, 5.43, 6.44, 6.49, and 6.26 mm/year for Ale, Yayu, Gera, Goma, and Limu Seka respectively, accompanied by year-to-year variability. Maximum and minimum temperatures exhibited a similar increasing trend and year-to-year variability across all study sites and altitude zones. Minimum temperature increased at a similar rate of 0.2 °C per decade in all districts, while maximum temperature increased at a rate of 0.2 °C/decade for Ale and 0.3 °C /decade in Gera, Goma, Limu Seka, and Yayu. High- and mid-altitude areas of three of our study sites (Ale, Gera, and Goma) are already experiencing conditions outside optimal coffee production ranges, as rainfall has exceeded ideal conditions. Should the current trends persist, however, other areas are at risk, as rising variability in the mean amount of rainfall and temperature can disrupt coffee phenological stages, reducing yield and quality. The increasing trend of maximum and minimum temperatures has already been identified as a threat to lowland and midland coffee-producing areas, with some hoping that the highlands might be a refuge for coffee production in the future. Unfortunately, changing rainfall patterns also threaten coffee production in the highlands in our study areas. Our results suggest the importance of local-scale analysis and a clear understanding of specific contexts using fine-resolution gridded climate datasets in areas where weather stations are scant and sparsely distributed.

Near-surface PM2.5 concentrations have been greatly exacerbated by urban land expansion and dense urban traffic. This study aims to clarify the effects of multiple factors on near-surface PM2.5 concentrations from three perspectives of background climatic variables, urban morphology variables, and traffic-related emission intensity. First, two case areas covering multiple local blocks were selected to conduct mobile measurements under different climatic conditions. The observed meteorological parameters and PM2.5 concentration were obtained through GIS-based imaging. These interpolation results of air temperature and relative humidity reveal highly spatiotemporal diversity, which is greatly influenced by artificial heat emissions and spatial morphology characteristics in local areas. The PM2.5 concentration on measurement days also varies considerably from the lowest value of 44~56 μg/m3 in October to about 500 μg/m3 in December in Harbin winter and ranges between about 5 μg/m3 and 50 μg/m3 in Guangzhou summer. The correlation analysis reveals that both the climatic conditions and urban morphology characteristics are significantly correlated with local PM2.5 concentration. Especially for Guangzhou summer, the PM2.5 concentration was positively correlated with the street traffic emission source intensity with correlation coefficient reaching about 0.79. Multivariate nonlinear formulas were applied to fit the association between these factors and PM2.5 concentration with higher determined coefficients. And optimization strategies are thus suggested to improve the urban air quality in local-scale areas. This attribution analysis contributes to environmentally friendly urban construction. [ABSTRACT FROM AUTHOR]

Grazing exclusion (GE) and rest grazing (RG) are important management systems for the restoration of degraded grassland ecosystems. In order to evaluate the effects and mechanisms of different grazing management systems on the scale dependency of species diversity, plant community indices and soil variables were determined in 32 plots in the Qilian Mountains in Gansu Province. The results show that diversity effects and their regulating mechanisms had space-scale dependence under different grazing management systems. The species richness and species diversity indices of RG grassland were significantly higher than those of GE at the regional scale. Species richness for RG and GE plots was 128 and 98, respectively, and the Shannon–Wiener and Simpson indices for RG and GE plots were 2.26 and 2.16, and 0.85 and 0.83, respectively. Additionally, three grazing management systems had a significant effect on species richness in mountain meadows, but different management systems had significantly different effects on species diversity indices in mountain meadows and temperate steppes. Meanwhile, soil variables only influenced species diversity at the regional scale. Most of the plant and soil variables at each scale had positive effects on species diversity. However, a negative correlation was seen between biodiversity and species coverage, mean plant height, soil porosity (SP) and bulk density (BD) under the two contrasting grazing management systems. In conclusion, choosing RG at the regional scale and selecting grazing management systems according to different grassland types at the local scale can help to restore degraded grassland vegetation. [ABSTRACT FROM AUTHOR]

Context and objectives: Climate extremes associated with wet and dry conditions are one of the main causal elements of the disasters that adversely impact Uganda's agriculturally based economy. However, the lack of reliable forecast records for wet and dry conditions remains a challenge at a local scale. Given the proliferation of geostatistical forecast algorithms, this study assessed the suitability of three forecast algorithms: forest-based, exponential smoothing and curve fitting in forecasting wet and dry conditions at a local scale in Uganda. Methodology: The CHIRPS satellite gridded datasets for the variable short rains season of September, October, and November (SON) for the 1981-2020 historical period were used to develop the forecasts and the 2021-2022 period was used to validate the forecasts. The Standardized Precipitation Index (SPI) derived from the CHIRPS dataset was used as the proxy for wet and dry conditions. The three algorithms were assessed by subjecting them to the SPI space-time cube structure in the ArcGIS environment. Using the resultant Forecast and Validation Root Mean Square Error (FRMSE and VRSME respectively), forecast models were then generated for each of the algorithms. A comparison of the least VRSME at every locality from any of the three algorithms was then used to build a joint forecast model. Results: Results from the three algorithms demonstrate that each locality experiences an independent forecast regardless of the influence of the immediate neighbourhood, and by 2025, the majority of the localities will experience moderately wet conditions during the SON season. The forest-based forecast, exponential smoothing, curve fitting and the combined least VRMSE forecast produced a best value of R2=0.33, 0.48, 0.4 and 0.62 respectively upon validation of the exact value. However, for values within the 95% confidence interval band, an R2 =0.89, 0.83 was realized for the forest-based and exponential smoothing. Based on the behavioural performance of the algorithms, results further reveal that most of the localities in the study area exhibit complex patterns and can best be predicted by forest-based algorithms. The results from this study support the motive of the Sustainable Development Goal (SDG) 13 by enabling the communication of empirical studies on locally determined climate contributions. The knowledge gained regarding localized wet and dry conditions prediction will help to increase the capacity of local governance and decision-making organizations that adopt and put into practice local disaster risk reduction initiatives. Further research is needed to assess the driving factors behind the pattern behaviours at the different localities. [ABSTRACT FROM AUTHOR]

Founded in the countryside an hour from Bordeaux, France, by Thích Nhät Hcnh, known for his engaged and modern Buddhism, Plum Village is famous throughout the world for its mindfulness meditation retreats. Although many studies have been carried out on Thích Nhất Hạnh's history and spirituality, none has addressed the question of the territorial implantation of Plum Village on a local scale, nor the processes of the worldwide diffusion of its network. After presenting the context of the penetration of Thích Nhất Hạnh's teaching in the West, I explore the establishment of an exogenous religious community in the French countryside in terms of otherness and analyse the communication at play in the process of integration into the local scale in its municipalities in New Aquitaine, and then look at the strategy and means of communication put in place to to federate and expand its network on a global scale. [ABSTRACT FROM AUTHOR]

Seagrasses provide diverse ecosystem services that support communities, yet, they are among the most threatened marine habitats. Efforts to conserve and sustainably manage seagrasses are increasing, particularly amidst the era of climate change, in which they play a critical role. However, these activities often received less attention or were slow in gaining momentum partly due to a lack of societal recognition of seagrasses and their importance. Thus, in this study, we collected community perceptions of seagrass ecosystem services and threats from 391 respondents in Karimunjawa National Park (KNP), a nationally declared protected area in Indonesia. We aim to provide insights on people's recognition of seagrasses from a local scale with strict protection measures. Overall, respondents showed varying perceptions of seagrass ecosystem services, with provisioning services more highly perceived than regulating services. The perceived level of threats was inconclusive, though, reclamation along shorelines received higher rates (leaning toward most damaging) than other threats such as natural disasters and illegal fishing activities. Sociodemographic attributes of respondents were found to influence their perceptions, with occupation as the most pronounced driving factor. The variations observed in seagrass perceptions suggest that there is a need to strengthen and/or enhance seagrass awareness and education campaigns, which is in line with the increasing demand that public perceptions matter for the conservation and sustainable management of seagrass ecosystems. We presented here the use and insights of community perceptions for seagrass blue carbon conservation in KNP, and consequently in Indonesia, where seagrass meadows are considered globally important carbon sinks. [ABSTRACT FROM AUTHOR]

Based on air quality data from dense local micro-stations and sparse national stations, and meteorological data, this study examined the temporal and spatial patterns of air pollution during the Spring Festival in Xiangyang using high-frequency spatial analysis, correlation analysis, and pollutant concentration comparison. The implementation effect of a policy banning fireworks and firecrackers during the Spring Festival was evaluated. The results showed that during the Spring Festival in 2018, the weather in Xiangyang was relatively stable, and the air quality was generally poor. Owing to the influence of fireworks and firecrackers set off from New Year's Eve to the first day of the Lunar New Year in the peripheral areas of Xiangyang, the air pollution condition shifted from mild to severe. The concentrations of PM2.5 and PM10 increased gradually from 19:00 on New Year's Eve, rose linearly after 00:00 on the first day of the Lunar New Year, and then reached a peak during the Spring Festival at 08:00. During this period, the concentrations of SO2 and NO2 also increased significantly, whereas that of CO had no obvious regularity. During the Spring Festival, the spatial distribution patterns of PM2.5 and PM10 daily average concentrations showed a moderate or higher pollution trend of "high in the South and low in the North" on New Year's Eve and the second to fifth days of the Lunar New Year, with Hanjiang and Tangbai Rivers as the boundaries. On the first and sixth days of the Lunar New Year, air pollutants covered almost all of Xiangyang. The setting off of fireworks and firecrackers in the surrounding areas is the primary cause of the heavily polluted weather from New Year's Eve to the first day of the Lunar New Year, and until the fourth day. Traffic exhaust, road dust, and cooking fumes remain significant sources of air pollutants in Xiangyang during the Spring Festival. The characteristic geographical environment and variable meteorological elements are important factors that cause air pollution. Owing to the continuous adoption of air pollution prevention and control policies over the past four years, the overall air pollution situation has improved in Xiangyang. The scope of the firework bans was gradually expanded, thus effectively improving the overall air quality. Compared with research on urban air pollution using a small number of monitoring stations, the application of a high-density air quality monitoring network can describe in detail the spatio-temporal distribution characteristics of urban air pollution on a local scale. Accordingly, increasing the frequency of the spatial analysis of air pollution can allow for the deduction of the specific evolutionary process of air pollution in space. Particularly in special periods or polluted weather, a precise understanding of the spatio-temporal evolution of air pollution can provide an important basis and reference for the prevention and control of urban air pollution.

At present the digital divide has started to be considered not so much in the context of Internet access itself or the skills of Internet users, but in terms of Internet performance. The COVID-19 pandemic has revealed that faster Internet made it easier to adapt to the new reality. But not all areas can benefit from good Internet connection. Therefore, the aim of this study is to identify spatial regularities in Internet performance on a local scale. This study is based on a set of data generated by Internet users, collected using the publicly available Ookla Speedtest measurement tool. The information about Internet speed and latency obtained in this way shows the actual Internet speed experienced. The analyses have indicated significant characteristics of the spatial differentiation of Internet performance. First, in the case of the Internet, the core-periphery dimension is not universal and obvious, as regional systems are strongly marked. Second, perceiving the digital divide mainly through the prism of Internet access is an insufficient approach.

[Display omitted] The use of remote sensing data methods is affordable for the mapping of soil properties of the plowed layer over croplands. Carried out in the framework of the ongoing STEROPES project of the European Joint H2020 Program SOIL, this work is focused on the feasibility of Sentinel-2 based approaches for the high resolution mapping of topsoil clay and organic carbon (SOC) contents at the within-farm or within-field scales, for cropland sites of contrasted climates and soil types across the Northern hemisphere. Four pixelwise temporal mosaicking methods, using a two years-Sentinel-2 time series and several spectral indices (NDVI, NBR2, BSI, S2WI), were developed and compared for i) pure bare soil condition (maxBSI), ii) driest soil condition (minS2WI), iii) average bare soil condition (Median) and iv) dry soil conditions excluding extreme reflectance values (R90). Three spectral modeling approaches, using the Sentinel-2 bands of the output temporal mosaics as covariates, were tested and compared: (i) Quantile Regression Forest (QRF) algorithm; (ii) QRF adding longitude and latitude as covariates (QRFxy); (iii) a hybrid approach, Linear Mixed Effect Model (LMEM), that includes spatial autocorrelation of the soil properties. We tested pairs of mosaic and spectral approaches on ten sites in Türkiye, Italy, Lithuania, and USA where soil samples were collected and SOC and clay content were measured in the lab. The average RPIQ of the best performances among the test sites was 2.50 both for SOC (RMSE = 0.15%) and clay (RMSE = 3.3%). Both accuracy level and uncertainty were mainly influenced by site characteristics of cloud frequency, soil types and management. Generally, the models including a spatial component (QRFxy and LMEM) were the best performing, while the best spatial mosaicking approaches mostly were Median and R90. The most frequent optimal combination of mosaicking and model type was Median or R90 and QRFxy for SOC, and R90 and LMEM for clay estimation. [ABSTRACT FROM AUTHOR]

Background: For more than 20 years, restoration measures have been conducted on watercourses in Germany to increase habitat diversity and thus promote biodiversity. However, their ecological efficacy often proved to be limited. While some studies report an increase in species diversity, others show little evidence of improvement even many years after the implementation of restoration measures. In general, ecological efficacy of hydromorphological restoration measures is highest for terrestrial and semiaquatic groups of organisms such as floodplain vegetation and ground beetles. According to the literature, macrophytes responded most strongly to in-stream restoration measures, while fish stocks showed little improvement and macroinvertebrates showed little or no effect in terms of species richness and diversity. These findings raise the question of reasons for the low ecological efficacy of hydromorphological restoration measures, especially for macroinvertebrate communities. The following literature review and a case study for the river Horloff will provide possible indications for failing success of intensive restoration measures. Results: One reason for the inadequate ecological status of many restored river stretches is the inappropriate scaling of restoration measures. Often, small-scale restoration measures are planned, although the respective water bodies exhibit stressors at the catchment scale that impair the ecological efficacy of restoration measures. In particular, chemical contamination of running waters is often insufficiently addressed in the planning and implementation of restoration measures and hampers efficacy of hydromorphological restoration measures. For a holistic water resource management, the planning and implementation of measures should therefore be more closely coordinated and harmonized between federal states and neighboring countries. For this purpose, the establishment of so-called river basin communities is suitable, as they already exist today on the rivers Rhine, Danube, Meuse, Weser, Elbe, Ems, Eider, Schlei/Trave, Warnow/Peene. Conclusion: The literature review indicated that for a successful recolonization of restored river stretches by macroinvertebrates and the enhancement of the ecological status, large-scale stressors, i.e., stressors acting at the catchment scale, should be eliminated initially by restoration measures focusing on the chemical contamination and the surrounding land use. Structural restoration measures acting on the reach or local scale should ideally be implemented contemporarily to the removal of large-scale stressors like chemical contamination. [ABSTRACT FROM AUTHOR]

One method of understanding landscape pattern changes is through an understanding of land use/land cover (LULC) changes, which are closely related to landscape pattern changes. Previous studies have monitored LULC changes across North Korea but did not consider landscape changes at a local scale. Using multiple LULC products to construct sample points, the LULC was classified using a random-forest algorithm and Landsat satellite dataset. The overall accuracy of the classification was 97.66 ± 1.36%, and the Kappa coefficient was 0.95 ± 0.03. Based on the classification results, landscape indices were used to quantify and monitor landscape pattern changes. The results showed that, from 2000 to 2020, there was an increasing trend in built-up and forest areas in Pyongyang, while cropland showed a decreasing trend, and landscape fragmentation increased. However, urban expansion was not the main factor affecting fragmentation. The main factors were forest recovery and cropland reduction, leading to an increase in landscape fragmentation in Pyongyang. [ABSTRACT FROM AUTHOR]

Introduction: Rhizosphere microbes perform critical functions for their hosts, and their structure is strongly influenced by vegetation type. Although studies on the effects of vegetation on rhizosphere microbial community structure have been conducted at large and global environment scales, studies at local environment scales would eliminate numerous external factors such as climate and soil type, while highlighting the potential influence of local vegetation type. Methods: Here, we compared rhizosphere microbial communities using 54 samples under three vegetation types (herb, shrubs, and arbors, with bulk soil as the control) at the campus of Henan University. 16S rRNA and ITS amplicons were sequenced using Illumina high throughput sequencing. Results and Discussion: Rhizosphere bacterial and fungal community structures were influenced considerably by vegetation type. Bacterial alpha diversity under herbs was significantly different from that under arbors and shrubs. The abundance of phyla such as Actinobacteria was extremely higher in bulk soil than in the rhizosphere soils. Herb rhizosphere harbored more unique species than other vegetation type soils. Furthermore, bacterial community assembly in bulk soil was more dominated by deterministic process, whereas the rhizosphere bacterial community assembly was dominated by stochasticity and the construction of fungal communities was all dominated by deterministic processes. In addition, rhizosphere microbial networks were less complex than bulk soil networks, and their keystone species differed based on vegetation type. Notably, bacterial community dissimilarities were strongly correlated with plant phylogenetic distance. Exploring rhizosphere microbial community patterns under different vegetation types could enhance our understanding of the role of rhizosphere microbes in ecosystem function and service provision, as well as basic information that could facilitate plant and microbial diversity conservation at the local environment scale. [ABSTRACT FROM AUTHOR]

Satellite-observed night-time light (NTL) data provide a measure of the lighting brightness seen from space at different times and spatial and temporal resolutions, thus offering opportunities to explore them in many applications at different spatial locations (global, regional, local). However, most applications to date have been at relatively large spatial scales, despite the need to measure indicators at a local level. This paper sets out an analysis of the potential of NTL data for populating indicators at more local (neighbourhood, street) scales. We first reviewed the overall potential of NTL data for social indicators at different spatial scales by using a systematic search of the literature and applying the Maturity Matrix Framework (MMF). We also explored a case study (Durango State, Mexico) using Visible Infrared Imaging Radiometer Suite (VIIRS) imageries, other geospatial data, and the social gap index (SGI) to identify social gaps at the local scale. The literature review showed that NTL can play a role in supporting 49 out of 192 sustainable development goal (SDG) indicators having a focus on social issues, but most of these have been explored at the global or country scales. In the case study, we found that low radiance is indeed associated with higher SGI levels (i.e., more social deprivation) and vice versa. However, more research is needed from other contexts to support a link between NTL radiance levels and social indicators at local scales. [ABSTRACT FROM AUTHOR]

The assessment of vulnerability to the danger of flooding, with a focus on the need for rescue and assistance from the population, is still in an exploratory scientific phase. The main objective of this research is to propose a methodology based on the issues of rescue and assistance in the face of the risk of floods and to provide a tool for its management. A series of maps is presented, indicating those territorial elements that require rescue and surveillance in a prioritized manner in a visual and accessible way for public administration. Four methodological cartographic proposals have been designed as follows: (1) a map of territory sectors with special rescue needs (dependent population and/or buildings without shelter); a map of the impact on transportation infrastructure and vulnerable areas of buildings (2); a map of vulnerability to possible disorder and looting caused by flooding events (3); and a map of the increase in the cost of deployment for rescue and assistance systems (4). As an experimental zone to test the effectiveness of these proposals, a peri-urban area of the municipality of Málaga (Spain) is chosen, which has an extensive history of severe floods. The results confirm the applied and preventive nature of the tool, which can be incorporated into flood risk management plans and local flood risk action plans developed by public administrations. The main finding of the research is the technical advancement that comes with a precise understanding of vulnerability and its resulting issues for better flood risk management.

It is hypothesised that ecological restoration in grasslands can induce an alternative stable state shift in vegetation. The change in vegetation influences insect community assemblages and allows for greater functional redundancy in pollination and refuge for native insect species. 2. Insect community assemblages at eight coastal California grassland sites were evaluated. Half of these sites had undergone restoration through active revegetation of native grassland flora and half were non-restored. Insects were collected from Lupinus bicolor (Fabaceae) within 2 × 2-m2 plots in spring 2017. Lupinus bicolor is a common native species that is used in California restoration projects, and home and state landscaping projects. 3. Ordination demonstrated that insect community assemblages were different between restored and non-restored sites. These differences were seen in insect functional groups as well as taxa-specific differences and were found to be driven by environmental characteristics such as non-native forb cover. 4. Functional redundancy of herbivores decreased at restored sites, while pollinators became more redundant compared with non-restored sites. The assemblages of the common species found at restoration sites contained more native insects than those found at non-restored sites, including species such as Bombus vosnesenskii. 5. Local grassland restoration has the potential to induce an alternative stable state change and affect insect community assemblages. Additionally, it was found that grassland restoration can be a potential conservation tool to provide refugia for bumblebees (Bombus), but additional studies are required to fully understand its broader applicability.

The ecology of benthic diatoms is scarce in diatom reviews, and it seems that the loss of interest in their local ecology (populations–communities) coincides with an increase in metacommunity studies. We include a review of the latter to highlight some unresolved issues. We aim to demonstrate the relevance of local population–community ecology for a better understanding of the metacommunity by addressing gaps such as the relevance of biotic relationships. We analyzed 132 assemblages of benthic diatoms from two neighboring catchments, with varying altitudes, lentic and lotic waters and substrates. Population–community features (e.g., populations' relative abundance and alpha diversity) and metacommunity descriptors (e.g., beta diversity indices) were related to likely control factors such as space, catchment features, local physico-chemistry and biotic environment. Our results confirm the relevant role of local interactions between diatoms and with the biotic environment as the mechanism in assembly communities. Moreover, abiotic habitat stability enhances alternative assemblages, which are the base of the metacommunity structure, mostly by taxa sorting and mass effects. Our results suggest that in order to better disclose factors controlling metacommunities, we must study their communities at local scales where mechanisms that explain their assemblage occur, as this is the bridge to a better understanding of benthic diatom ecology. [ABSTRACT FROM AUTHOR]

Floods cause severe damage to people as well as to properties. The same flood can cause different levels of damage to different households, but investigations into floods tend to be conducted on regional and national scales, thereby missing these local variations. It is therefore necessary to understand individual experiences of flood damage to implement effective flood management strategies on a local scale. The main objectives of this study were to develop a model that represents the relationship between socioeconomic conditions and flood damage at a local scale, and to understand the socioeconomic factors most closely tied to flood damage. The analysis is novel in that it considers not only the impact of flood characteristics, but also the impact of social, economic, and geographic factors on flood damage. This analysis derives from a quantitative modeling approach based on community responses, with the responses obtained through questionnaire surveys that consider four consecutive floods of differing severity. Path analysis was used to develop a model to represent the relationships between these factors. A randomly selected sample of 150 data points was used for model development, and nine random samples of 150 data points were used to validate the model. Results suggest that poor households, located in vulnerable, low‐lying areas near rivers, suffer the most from being exposed to frequent, severe floods. Further, the results show that the socioeconomic factors with the most significant bearing on flood damage are per capita income and geographic location of the household. The results can be represented as a cycle, showing that social, economic, geographic, and flood characteristics are interrelated in ways that influence flood damage. This empirical analysis highlights a need for local‐scale flood damage assessments, as offered in this article but seldom seen in other relevant literature. Our assessment was achieved by analyzing the impact of socioeconomic and geographic conditions and considering the relationship between flood characteristics and flood damage. [ABSTRACT FROM AUTHOR]

Grazing exclusion (GE) and rest grazing (RG) are important management systems for the restoration of degraded grassland ecosystems. In order to evaluate the effects and mechanisms of different grazing management systems on the scale dependency of species diversity, plant community indices and soil variables were determined in 32 plots in the Qilian Mountains in Gansu Province. The results show that diversity effects and their regulating mechanisms had space-scale dependence under different grazing management systems. The species richness and species diversity indices of RG grassland were significantly higher than those of GE at the regional scale. Species richness for RG and GE plots was 128 and 98, respectively, and the Shannon–Wiener and Simpson indices for RG and GE plots were 2.26 and 2.16, and 0.85 and 0.83, respectively. Additionally, three grazing management systems had a significant effect on species richness in mountain meadows, but different management systems had significantly different effects on species diversity indices in mountain meadows and temperate steppes. Meanwhile, soil variables only influenced species diversity at the regional scale. Most of the plant and soil variables at each scale had positive effects on species diversity. However, a negative correlation was seen between biodiversity and species coverage, mean plant height, soil porosity (SP) and bulk density (BD) under the two contrasting grazing management systems. In conclusion, choosing RG at the regional scale and selecting grazing management systems according to different grassland types at the local scale can help to restore degraded grassland vegetation.

Near-surface PM2.5 concentrations have been greatly exacerbated by urban land expansion and dense urban traffic. This study aims to clarify the effects of multiple factors on near-surface PM2.5 concentrations from three perspectives of background climatic variables, urban morphology variables, and traffic-related emission intensity. First, two case areas covering multiple local blocks were selected to conduct mobile measurements under different climatic conditions. The observed meteorological parameters and PM2.5 concentration were obtained through GIS-based imaging. These interpolation results of air temperature and relative humidity reveal highly spatiotemporal diversity, which is greatly influenced by artificial heat emissions and spatial morphology characteristics in local areas. The PM2.5 concentration on measurement days also varies considerably from the lowest value of 44~56 μg/m3 in October to about 500 μg/m3 in December in Harbin winter and ranges between about 5 μg/m3 and 50 μg/m3 in Guangzhou summer. The correlation analysis reveals that both the climatic conditions and urban morphology characteristics are significantly correlated with local PM2.5 concentration. Especially for Guangzhou summer, the PM2.5 concentration was positively correlated with the street traffic emission source intensity with correlation coefficient reaching about 0.79. Multivariate nonlinear formulas were applied to fit the association between these factors and PM2.5 concentration with higher determined coefficients. And optimization strategies are thus suggested to improve the urban air quality in local-scale areas. This attribution analysis contributes to environmentally friendly urban construction.

With the development of medium- and high-resolution satellites, successfully segmenting differently sized geo-objects remains a challenging issue for geographic object-based image analysis (GEOBIA). The hybrid image segmentation method is a good alternative to produce good segmentation that best matched the different sizes of geo-objects. However, the existing methods almost use segmentation parameters (SPs), such as scale, to control the sizes and shapes of segments. This will lead to two issues: (1) one single scale is impossible to segment every geo-object well due to the land cover complexity within remote-sensing imageries; (2) over- and under-segmented regions still occur in the segmentation results, whatever using any advanced segmentation methods. To solve the above problems, this paper developed a hybrid image segmentation method with local scale-guided hierarchical region merging and further over- and under-segmentation processing. First, the primitive segmentation was produced and then stratified into layers with different land covers. Then, the local scale was calculated for a more objective merging process in the separating layers. Third, the over- and under-segmentation at separating layers was recognized and re-processed for achieving a fine segmentation. To validate the proposed method, it was applied to three test images of gaofen-1 satellite with different land cover types, and ten competing methods were compared. The visual and quantitative results indicated the advantage of our method in segmenting out different sizes of geo-objects, which can effectively reduce the over- and under-segmentation error.

Wildfire risk assessment provides important tools to fire management, by analysing and aggregating information regarding multiple, interactive dimensions. The three main risk dimensions hazard, exposure and vulnerability, the latter considered in its social dimension, were quantified separately at the local scale for 972 civil parishes in central mainland Portugal and integrated into a wildfire risk index. The importance of each component in the level of risk varied, as assessed by a cluster analysis that established five different groups of parishes, each with a specific profile regarding the relative importance of each dimension. The highest values of wildfire risk are concentrated in the centre-south sector of the study area, with high-risk parishes also dispersed in the northeast. Wildfire risk level is dominated by the hazard component in 52% of the parishes, although with contrasting levels of magnitude. Exposure and social vulnerability dominate together in 32% of the parishes, with the latter being the main risk driver in only 17%. The proposed methodology allows for an integrated, multilevel assessment of wildfire risk, facilitating the effective allocation of resources and the adjustment of risk reduction policies to the specific reality in each parish that results from distinct combinations of the wildfire risk dimensions. [ABSTRACT FROM AUTHOR]

Based on air quality data from dense local micro-stations and sparse national stations, and meteorological data, this study examined the temporal and spatial patterns of air pollution during the Spring Festival in Xiangyang using high-frequency spatial analysis, correlation analysis, and pollutant concentration comparison. The implementation effect of a policy banning fireworks and firecrackers during the Spring Festival was evaluated. The results showed that during the Spring Festival in 2018, the weather in Xiangyang was relatively stable, and the air quality was generally poor. Owing to the influence of fireworks and firecrackers set off from New Year's Eve to the first day of the Lunar New Year in the peripheral areas of Xiangyang, the air pollution condition shifted from mild to severe. The concentrations of PM2.5 and PM10 increased gradually from 19:00 on New Year's Eve, rose linearly after 00:00 on the first day of the Lunar New Year, and then reached a peak during the Spring Festival at 08:00. During this period, the concentrations of SO2 and NO2 also increased significantly, whereas that of CO had no obvious regularity. During the Spring Festival, the spatial distribution patterns of PM2.5 and PM10 daily average concentrations showed a moderate or higher pollution trend of "high in the South and low in the North" on New Year's Eve and the second to fifth days of the Lunar New Year, with Hanjiang and Tangbai Rivers as the boundaries. On the first and sixth days of the Lunar New Year, air pollutants covered almost all of Xiangyang. The setting off of fireworks and firecrackers in the surrounding areas is the primary cause of the heavily polluted weather from New Year's Eve to the first day of the Lunar New Year, and until the fourth day. Traffic exhaust, road dust, and cooking fumes remain significant sources of air pollutants in Xiangyang during the Spring Festival. The characteristic geographical environment and variable meteorological elements are important factors that cause air pollution. Owing to the continuous adoption of air pollution prevention and control policies over the past four years, the overall air pollution situation has improved in Xiangyang. The scope of the firework bans was gradually expanded, thus effectively improving the overall air quality. Compared with research on urban air pollution using a small number of monitoring stations, the application of a high-density air quality monitoring network can describe in detail the spatio-temporal distribution characteristics of urban air pollution on a local scale. Accordingly, increasing the frequency of the spatial analysis of air pollution can allow for the deduction of the specific evolutionary process of air pollution in space. Particularly in special periods or polluted weather, a precise understanding of the spatio-temporal evolution of air pollution can provide an important basis and reference for the prevention and control of urban air pollution. [ABSTRACT FROM AUTHOR]

In the last few decades, urban planning has expanded regarding environmental considerations. However, air quality, which is regarded as an important aspect of the green development of cities, is not considered in urban planning. This research aims to propose a tool to easily introduce air quality considerations into urban projects. Nowadays, the usual air pollutants (NOx, PM, SO2, and O3) are measured via sophisticated monitoring stations—or even low-cost devices—to give near-real-time air quality indices. However, stations are not adapted to local air pollution and real-time data are not helpful for planning purposes. An index able to rank areas and projects based on urban "air proxy data" would help decision makers. This paper presents how to create an air quality index as a decision support tool for urban planning. No pollutant measurement campaign will be necessary and only data that are easily accessible, even to nonexperts, are used. This paper describes the methodological development of an index that we call AQOI (Air Quality Observed Index), and the results obtained for four different locations (industrial, urban, and rural) considered as preliminary tests. [ABSTRACT FROM AUTHOR]

Abstract Habitat selection and spatial usage are important components of animal behavior influencing fitness and population dynamic. Understanding the animal–habitat relationship is crucial in ecology, particularly in developing strategies for wildlife management and conservation. As this relationship is governed by environmental features and intra‐ and interspecific interactions, habitat selection of a population may vary locally between its core and edges. This is particularly true for central place foragers such as gray and harbor seals, where, in the Northeast Atlantic, the availability of habitat and prey around colonies vary at local scale. Here, we study how foraging habitat selection may vary locally under the influence of physical habitat features. Using GPS/GSM tags deployed at different gray and harbor seals’ colonies, we investigated spatial patterns and foraging habitat selection by comparing trip characteristics and home‐range similarities and fitting GAMMs to seal foraging locations and environmental data. To highlight the importance of modeling habitat selection at local scale, we fitted individual models to colonies as well as a global model. The global model suffered from issues of homogenization, while colony models showed that foraging habitat selection differed markedly between regions for both species. Despite being capable of undertaking far‐ranging trips, both gray and harbor seals selected their foraging habitat depending on local availability, mainly based on distance from the last haul‐out and bathymetry. Distance from shore and tidal current also influenced habitat preferences. Results suggest that local conditions have a strong influence on population spatial ecology, highlighting the relevance of processes occurring at fine geographical scale consistent with management within regional units.

The life expectancy of societies has grown as a result of more active and healthier lifestyles, as has the proportion of the elderly population. This situation triggered the graying of the society and the work of different disciplines on the subject. On the other hand, the mobility of an aging population has become a topic of transportation, and policies for elderly people, particularly in the West, have acquired prominence. This study examines transportation policies for the elderly on a local scale through the study area. The mobility requirements of the elderly, user subgroups, transportation policies, and transportation applications for these policies were investigated in this context, as well as how neighborhood-based practices in the Beşiktaş district would alter geographically. Levels of accessibility and availability, which stand out in the transportation needs of the elderly, were assessed on the basis of district neighborhoods using GIS analyses. Following the analyses, it was discovered that the neighborhoods in need of assistance are clustered in three main regions: Kuzey Beşiktaş, Hilal, and Beşiktaş Bazaar. Arnavutköy distinguishes out among the neighborhoods in terms of transportation applications. The study revealed that although the transportation policies for the elderly are determined throughout the district, the practices vary at lower scales. [ABSTRACT FROM AUTHOR]

A capability for mapping meter-level resolution soil moisture with frequent temporal sampling over large regions is essential for quantifying local-scale environmental heterogeneity and eco-hydrologic behavior. However, available surface soil moisture (SSM) products generally involve much coarser grain sizes ranging from 30 m to several 10 s of kilometers. Hence, a new method is proposed to estimate 3-m resolution SSM using a combination of multi-sensor fusion, machine-learning (ML), and Cumulative Distribution Function (CDF) matching approaches. This method established favorable SSM correspondence between 3-m pixels and overlying 9-km grid cells from overlapping Planet SuperDove (PSD) observations and NASA Soil Moisture Active-Passive (SMAP) mission products. The resulting 3-m SSM predictions showed improved accuracy by reducing absolute bias and RMSE by ~0.01 cm3/cm3 over the original SMAP data in relation to in situ soil moisture measurements for the Australian Yanco region while preserving the high sampling frequency (1–3 day global revisit) and sensitivity to surface wetness (R 0.865) from SMAP. Heterogeneous soil moisture distributions varying with vegetation biomass gradients and irrigation regimes were generally captured within a selected study area. Further algorithm refinement and implementation for regional applications will allow for improvement in water resources management, precision agriculture, and disaster forecasts and responses. [ABSTRACT FROM AUTHOR]

Climate change is a concerning phenomenon worldwide. The reduction in greenhouse gas emissions is the core of the mitigation strategies that are effective countermeasures to address a changing climate in the long term. Nevertheless, the need for short-term solutions regarding adaptation to climate change (ACC) has gained growing interest in the scientific community and in European institutions. European and national ACC principles are being integrated in strategies and plans. In Italy, some regions have adopted ACC principles in strategic plans, which influence the whole local planning system and persuade local communities to become more climate-resilient. This study focuses on the mainstreaming of ACC into strategies, plans, programs, and projects (SPPPs) adopted by the following Italian cities: Bologna, Milan, Naples, Rome, Turin, and Venice. We scrutinize the contents of SPPPs with respect to four criteria: (i) references to strategies or plans for ACC; (ii) inclusion of ACC objectives and (iii) measures; and (iv) references to—or the inclusion of—climatic analysis on historical series and/or future projections. We found out that most SPPPs adopted by the cities have considered ACC in a promising way, i.e., all the cities are inclined to promote ACC, despite three of them lacking a municipal ACC strategy or plan and a National Adaptation Plan not being in force. [ABSTRACT FROM AUTHOR]

Extracting Total Precipitable Water Vapor (TPW) and its variations from the Moderate Resolution Imaging Spectroradiometer (MODIS) data on a local scale is challenging. Meta-heuristic algorithms have a high ability to solve complex engineering problems of hydrology and climatic studies. Hence, the present study extracts TPW values using meta-heuristic algorithms for MODIS surface reflectance data. In this regard, radiosonde observations of six stations in the western part of Iran during 2019 and 2020 were used as the ground truth data for training algorithms and evaluating the results. The results were also validated with Global Positioning System (GPS) TPW data of Tehran-Mehrabad station. Moreover, MODIS surface reflectance (MOD021) and cloud mask (MOD35) products were prepared to distinguish cloudy days from non-cloudy, along with MODIS TPW (MOD05) for corresponding dates. Meta-heuristic algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Harmony Search (HS), Invasive Weed Optimization (IWO), Gray Wolf Optimization (GWO), and Grasshopper Optimization Algorithm (GOA), were applied to improve the performance of MOD05 algorithm. The results showed the proper performance of all the selected algorithms. Nevertheless, the GOA algorithm acquired the best result. The Root Mean Square Error (RMSE) and R values obtained from comparing GOA results with radiosonde data were 2.96 mm and 0.82. Those values for comparing GOA results with GPS data were 2.94 mm and 0.83, respectively. However, MODIS TPW, RMSE, and R showed 6.53 mm and 0.69, respectively, compared to radiosonde data and 6.55 mm and 0.68 compared to GPS data. Overall, the results proved the proper performance of the used meta-heuristic algorithms in extracting TPW from MODIS measurements on a local scale. [ABSTRACT FROM AUTHOR]

Soil function degradation threatens the sustainable management of soil resources and soil organic matter (SOM) is a vital and important factor. Powerful measuring tools will become very important, especially in areas where data are poor or absent. The archive: China Soil Visible and Near Infrared (vis–NIR) Spectroscopy Library (CSSL) could help providea solution for less costly and fast measuring of SOM. The aim of this article was to compare SOM prediction performance according to three strategies: i) general global partial least squares regression (PLSR) using CSSL with and without spiking samples; ii) memory‐based learning (MBL) using CSSL with and without spiking samples; and iii) general PLSR using only spiking samples to predict soil organic matter in the target area. When using spiked subsets, we also investigated the prediction performance of the extra‐weighted (several copies) subsets. A series of spiking subsets were randomly selected from the total spiking samples, which were selected by conditioned Latin hypercube sampling (cLHS) from the target sites. We calculated only the mean squared Euclidean distance (msd) between the estimates density function (pds) of the principal components (PCs) of vis–NIR spectroscopy from the validation dataset and spiking subsets and statistically inferred the optimal sampling set size to be 30. Our study showed that global PLSR using CSSL spiked with the statistically optimal local samples can achieve higher predicted performance [with a mean root mean square error (RMSE) of 5.75]. MBL spiked with five extra‐weighted optimal spiking samples achieved the best accuracy with an RMSE of 3.98, an R2 of 0.70, a bias of 0.04, and an LCCC of 0.81. The msd is a simple and effective method to determine an adequate spiking set size using only vis–NIR data. These accurate predictions demonstrated the usefulness of statistically representative spiking and MBL for advanced large soil spectral libraries for SOM determination, which is currently lacking at large soil spectral libraries in use. [ABSTRACT FROM AUTHOR]

One method of understanding landscape pattern changes is through an understanding of land use/land cover (LULC) changes, which are closely related to landscape pattern changes. Previous studies have monitored LULC changes across North Korea but did not consider landscape changes at a local scale. Using multiple LULC products to construct sample points, the LULC was classified using a random-forest algorithm and Landsat satellite dataset. The overall accuracy of the classification was 97.66 ± 1.36%, and the Kappa coefficient was 0.95 ± 0.03. Based on the classification results, landscape indices were used to quantify and monitor landscape pattern changes. The results showed that, from 2000 to 2020, there was an increasing trend in built-up and forest areas in Pyongyang, while cropland showed a decreasing trend, and landscape fragmentation increased. However, urban expansion was not the main factor affecting fragmentation. The main factors were forest recovery and cropland reduction, leading to an increase in landscape fragmentation in Pyongyang.

Aim: Historical biogeography and community ecology both seek to uncover the patterns and processes governing the structure and composition of communities, though typically at different temporal and spatial scales. Recent work has called to integrate these two fields; however, it is typically assumed that history plays little role in assembling contemporary, local communities. We incorporated phylogeographic data into traditional metacommunity analyses of freshwater fish communities to analyse if history can shape local community structure. Location: Streams in the Nicaraguan Depression in north‐eastern Costa Rica. Taxon Freshwater fish communities. Methods: We sampled community composition in 14 streams of the San Juan River Basin during the dry season of 2019 and evaluated variability in community composition in response to local and landscape‐scale environmental variability, spatial distance and historic processes using redundancy analyses. We measured environmental and spatial variables using typical methods utilized in metacommunity studies and approximated the effects of history with samova genetic groupings of three livebearing fishes native to the area. We also used PERMANOVAs to test if community composition exhibits similar spatial structure as seen in the genetic data of the three livebearing fishes used as historical proxies. Results: Large‐scale patterns of genetic diversity predicted the patterns of local community diversity with community composition showing similar spatial structuring. Additionally, history variables were the only variables that significantly explained community composition and accounted for 20.6% of the total variability. Main Conclusions: Species‐specific incidence patterns within Costa Rican freshwater fish communities vary according to biogeographic history, indicating that history can impact local community assembly. These observed patterns are likely due to colonization history following eustatic sea level change. Phylogeography can bridge the gap between classical biogeography and community ecology by enhancing inferences regarding community assembly through time and space, therefore studies should incorporate both genetic and local community data when assessing community assembly. [ABSTRACT FROM AUTHOR]

Accurate subseasonal prediction of East Asian summer precipitation (EASP) requires a deep understanding of the origins of its intraseasonal variability (ISV). However, the relative contributions to the EASP ISV from local processes, tropical intraseasonal oscillation (ISO), and extratropical influence remain unknown. We conducted a set of numerical experiments with a grid nudging method to confirm the roles of external forcing from mid‐to‐high latitude wave trains and tropical ISO and quantify their relative contributions. The Community Earth System Model can reproduce realistic EASP ISV and associated preceding signals. The tropical and mid‐to‐high latitude forcings account for, respectively, 53% and 40% of the total variance for the two leading ISV modes of EASP. The tropical forcing contributes more significantly to the two leading modes (31% and 40%, respectively) compared to the extratropical forcing (24% and 15%). These external forcings mainly affect EASP regional averages rather than the values of local (grid) scale. Plain Language Summary: East Asian summer monsoon precipitation exhibits significant fluctuations on a 2–5‐week time scale beyond the synoptic scale. These fluctuations are called intraseasonal variability (ISV). Since East Asia is located in between the largest continent (Eurasia) and the largest ocean (the Pacific), its ISV is affected by the southeastward propagating high‐latitude disturbances (wave trains) and northwestward propagating tropical ISV. However, the relative roles of these outside influences have never been quantified. We applied a climate model that could reproduce realistic ISV and designed a suite of numerical experiments to quantitatively determine the contributions of these "external forcings" to the East Asian ISV. About one half of the total intraseasonal variance (a measure of ISV intensity) arises from the mid‐to‐high latitude and tropical forcings. Thus, accurate simulations of tropical ISV and mid‐to‐high latitude wave trains are critical for improving subseasonal prediction over East Asia. Key Points: Community Earth System Model performs well in simulating the leading intraseasonal variability (ISV) modes of East Asian summer precipitation (EASP) and their preceding tropical and mid‐to‐high latitude signalsTropical and mid‐to‐high latitude forcings together contribute half of the total variance of the two leading ISV modes of EASPExternal tropical and mid‐to‐high latitude forcings affect EASP ISV more apparently on a regional, rather than a local, spatial scale [ABSTRACT FROM AUTHOR]